Predictive accuracy not changed enough to shift clinical decisions

March 22, 2010

Dr. Ross Prentice Public Health Sciences Division

Recent findings show that breast cancer risk assessment models—which predict a woman’s chance of developing the cancer—do not perform better when they include common genetic variants recently linked to the disease. Based on the data, the recommendations for breast cancer screening or treatments remain unchanged for most women. The study results appeared last week in The New England Journal of Medicine.

In recent years, genome-wide association studies have identified multiple common genetic variants associated with breast cancer. The extent to which adding these variants to existing models could improve clinical recommendations had not been tested in a large population of women prior to this study, whose authors included Drs. Ross Prentice and Charles Kooperberg of the Public Health Sciences Division.

Dr. Charles Kooperberg
Public Health Sciences Division

“When we included these newly discovered genetic factors, we found some improvement in the performance of risk models for breast cancer, but it was not enough improvement to matter for the great majority of women,” said lead author Dr. Sholom Wacholder, senior investigator in the National Cancer Institute’s Division of Cancer Epidemiology and Genetics.

The researchers combined data from five women’s health studies, including the observational component of the Women’s Health Initiative (the Center is home to WHI’s coordinating center and one of its clinical sites). Collectively, these studies provided more reliable and accurate estimates than those available from any single study and included more than 5,500 breast cancer patients and nearly 6,000 women without cancer. The women were predominately white and between the ages of 50 and 79. The team assembled information for each participant on established risk factors and on 10 genetic variants found to be associated with breast cancer risk.

For most women in the study, using both a predictive model and genetic information did not change their estimated risk of developing breast cancer enough to influence clinical decision-making.

The authors emphasized that the genome-wide association studies represent an early stage in our understanding of the inherited components of breast cancer risk. “We can expect to identify more genetic determinants of breast cancer, and to learn more about those we have already found,” Wacholder said. “This information, along with our increasing knowledge of non-genetic factors, should allow us to steadily improve our risk prediction models for breast cancer.”